NVIDIA announced today that ACUSIM Software, a leading provider of computational fluid dynamics (CFD) solutions widely used by engineers and scientists involved in product design, has integrated support for NVIDIA Tesla 20-series GPUs into the company’s latest AcuSolve 1.8 release.

Performance tests of the general-purpose finite-element-based CFD flow solver have demonstrated up to a 2x boost in performance with the Tesla C2050 GPU processor, compared with the latest quad-core CPU running the same simulation.

AcuSolve is used in a broad range of mechanical design applications and deployed by research organizations and Fortune 500 companies including Bechtel, Chevron, John Deere, Procter & Gamble, Sanyo, Visteon and Whirlpool. They use CFD simulations to replace costly physical tests during product development, which leads to shorter design times and improved product quality.

"It’s always about computing speed," said Tom Lange, director of Modeling and Simulation at Procter & Gamble. "GPU-accelerated CFD allows for more realism, helping us replace slow and expensive physical learning cycles with virtual ones. This transforms engineering analysis from the study of failure to true virtual trial and error, and design optimization."

With the introduction of AcuSolve 1.8, industries ranging from automotive, aerospace and defense to consumer goods, bio-medical devices and energy production can now reduce CFD simulation times, enabling more and increasingly complex simulations to be carried out by tapping into the massively parallel CUDA computing architecture of NVIDIA Tesla GPUs.

"Customers can improve their competitive advantage through faster time-to-market, improved product quality and lower product development cost," said Dr. Farzin Shakib, founder and CEO of ACUSIM Software. "Our collaboration with NVIDIA has helped us explore and implement innovative approaches to advance on these performance goals for AcuSolve simulations."

ACUSIM has implemented a hybrid parallel scheme for AcuSolve that combines shared and distributed memory parallel processing in a single CFD simulation. The shared memory operations of AcuSolve are accelerated on Tesla GPUs using OpenMP standards, while the CPUs manage the distributed memory operations using message passing library standards. Using this heterogeneous processing scheme, AcuSolve essentially selects the right processor (GPU or CPU) for the right job by executing each operation on the compute device that will maximize overall parallel efficiency.

AcuSolve has also demonstrated efficient multi-GPU scalability enabling it to be deployed in systems containing multiple GPUs such as the Tesla S-series and M-series products for datacenter-class HPC installations.

"More and more scientists and engineers are embracing GPU computing to drive value and efficiency into their CAE workflows," said Andrew Cresci, general manager of vertical marketing, NVIDIA. "We are delighted with ACUSIM’s achievements and look forward to continued collaboration to bring additional performance benefits to our customers."